AI

Create a generative AI-based application builder assistant using Amazon Bedrock Agents | Amazon Web Services

Create a generative AI-based application builder assistant using Amazon Bedrock Agents | Amazon Web Services

In this post, we set up an agent using Amazon Bedrock Agents to act as a software application builder assistant. Agentic workflows are a fresh new perspective in building dynamic and complex business use- case based workflows with the help of large language models (LLM) as their reasoning engine or brain. These agentic workflows decompose the natural language query-based tasks into multiple actionable steps with iterative feedback loops and self-reflection to produce the final result using tools and APIs. Amazon Bedrock Agents helps you accelerate generative AI application development by orchestrating multistep tasks. Amazon Bedrock Agents uses the reasoning capability…
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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas | Amazon Web Services

Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas | Amazon Web Services

Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Conventional ML development cycles take weeks to many months and requires sparse data science understanding and ML development skills. Business analysts’ ideas to use ML models often sit in prolonged backlogs because of data engineering and data science team’s bandwidth and data preparation activities. In this post, we dive into a business use case for a banking institution. We will show you…
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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 1 | Amazon Web Services

From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 1 | Amazon Web Services

The AWS Generative AI Innovation Center (GenAIIC) is a team of AWS science and strategy experts who have deep knowledge of generative AI. They help AWS customers jumpstart their generative AI journey by building proofs of concept that use generative AI to bring business value. Since the inception of AWS GenAIIC in May 2023, we have witnessed high customer demand for chatbots that can extract information and generate insights from massive and often heterogeneous knowledge bases. Such use cases, which augment a large language model’s (LLM) knowledge with external data sources, are known as Retrieval-Augmented Generation (RAG). This two-part series…
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Super charge your LLMs with RAG at scale using AWS Glue for Apache Spark | Amazon Web Services

Super charge your LLMs with RAG at scale using AWS Glue for Apache Spark | Amazon Web Services

Large language models (LLMs) are very large deep-learning models that are pre-trained on vast amounts of data. LLMs are incredibly flexible. One model can perform completely different tasks such as answering questions, summarizing documents, translating languages, and completing sentences. LLMs have the potential to revolutionize content creation and the way people use search engines and virtual assistants. Retrieval Augmented Generation (RAG) is the process of optimizing the output of an LLM, so it references an authoritative knowledge base outside of its training data sources before generating a response. While LLMs are trained on vast volumes of data and use billions…
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Socure to Acquire Effectiv for $136M

Deal Creates the Market’s First Unified Identity, Fraud and Risk Decision Engine Consolidating a Fragmented Industry Landscape and Propels the Company into the $200B Enterprise Fraud Detection Market Socure, the leading provider of artificial intelligence for digital identity verification, fraud prevention and sanction screening, has signed an agreement to acquire Effectiv, a real-time risk decisioning company, for $136M. The acquisition is expected to close in November. This strategic acquisition pairs Socure’s best-in-class digital identity verification and fraud solutions with a developer-friendly AI orchestration and decisions platform – a combination of technology not held by a single competitor, and one that will elevate the way the market combats fraud and verifies identities across the entire customer…
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Transitioning from Amazon Rekognition people pathing: Exploring other alternatives | Amazon Web Services

Transitioning from Amazon Rekognition people pathing: Exploring other alternatives | Amazon Web Services

Amazon Rekognition people pathing is a machine learning (ML)–based capability of Amazon Rekognition Video that users can use to understand where, when, and how each person is moving in a video. This capability can be used for multiple use cases, such as for understanding: Retail analytics – Customer flow in the store and identifying high-traffic areas Sports analytics – Players’ movements across the field or court Industrial safety – Workers’ movement in work environments to promote compliance with safety protocols After careful consideration, we made the decision to discontinue Rekognition people pathing on October 31, 2025. New customers will not…
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Swiss Innovation Agency Funds LatticeFlow AI for Governance Platform

LatticeFlow AI, a Swiss leader in trustworthy, safe, and compliant AI, announced today that it has secured about USD 3M funding from the Swiss Innovation Agency (Innosuisse) to advance its innovative AI Assessments platform. As one of just 33 projects selected from 373 applications in the highly competitive Swiss Accelerator initiative, this funding underscores the platform’s strong innovation potential, market relevance, and significant commercial opportunities. The project also tackles a key challenge in the rapidly growing AI Trust, Risk, and Security Management (AI TRiSM) market, which is projected to surpass USD 8 billion by 2033. LatticeFlow´s AI project will introduce the…
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